Although correlation filter-based tracking method achieve competitive results both on accuracy and robustness

there is still a need to improve the overall tracking capability. Aiming at problem of kernelized correlation filter-based tracking algorithm in scale target variation and occlusion

present a multi-scale correlation tracker algorithm combined with support vector machine（ SVM） detector to solve the above problems. By introducing the scale factor into the kernel matrix to improve the performance of correlation filter processing scale transform.Train an online SVM detector to retrieve the target when the target occluded

and adaptively adjust the learning rate of the model. By comparing with the other five outstanding tracking algorithms. Experimental results show that the proposed approach can estimate the object state accurately and handle the object occlusion problem effectively.